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* Added energy usage fixture. Updated dashboard utils and unicode fixture with new method parameters. * Add energy fixture to tests/access_tests.py * Add energy fixture to tests/core_tests.py * Add energy fixture to tests/dashboard_tests.py * Add energy fixture to tests/datasets/api_tests.py * Add energy fixture to tests/db_engine_specs/base_engine_spec_tests.py * Add energy fixture to tests/import_export_tests.py * Add energy fixture to tests/model_tests.py * Add energy fixture to tests/query_context_tests.py * Add energy fixture to tests/security_tests.py * Add energy fixture to tests/charts/api_tests.py * Changed formatting of slices' parameters in energy usage fixture * Removed loading energy udage data from test conf file * Add energy fixture to tests/databases/api_tests.py * Fixes after review: removed isort:skip, load_charts->load_energy_charts, removed unused import. * Added energy fixture to tests/charts/commands_tests.py and retrieving proper Slice by name * Fixed charts/api_tests.py to use energy_usage from fixtures * Fixed datasets/commands_tests.py to retrieve dataset by name and use energy_usage fixture * Changed energy usage data to generated data and fixed chart tests which was checking energy usage data
Superset
A modern, enterprise-ready business intelligence web application.
Why Superset | Supported Databases | Installation and Configuration | Get Help | Contributor Guide | Resources | Superset Users
Screenshots & Gifs
Gallery
View Dashboards
Slice & dice your data
Query and visualize your data with SQL Lab
Visualize geospatial data with deck.gl
Choose from a wide array of visualizations
Why Superset
Superset provides:
- An intuitive interface to explore and visualize datasets, and create interactive dashboards.
- A wide array of beautiful visualizations to showcase your data.
- Easy, code-free, user flows to drill down and slice and dice the data underlying exposed dashboards. The dashboards and charts act as a starting point for deeper analysis.
- A state of the art SQL editor/IDE exposing a rich metadata browser, and an easy workflow to create visualizations out of any result set.
- An extensible, high granularity security model allowing intricate rules on who can access which product features and datasets. Integration with major authentication backends (database, OpenID, LDAP, OAuth, REMOTE_USER, ...)
- A lightweight semantic layer, allowing to control how data sources are exposed to the user by defining dimensions and metrics
- Out of the box support for most SQL-speaking databases
- Deep integration with Druid allows for Superset to stay blazing fast while slicing and dicing large, realtime datasets
- Fast loading dashboards with configurable caching
Supported Databases
Superset speaks many SQL dialects through SQLAlchemy - a Python SQL toolkit that is compatible with most databases. Here are some of the major database solutions that are supported:
A complete list of supported databases can be found here.
Installation and Configuration
Get Involved
- Ask and answer questions on StackOverflow
- Join our community's Slack and please read our Slack Community Guidelines
- Join our dev@superset.apache.org Mailing list
Contributor Guide
Interested in contributing? Check out our CONTRIBUTING.md to find resources around contributing along with a detailed guide on how to set up a development environment.
Resources
- Superset 101 -- Getting Started Guide (From Preset Blog)
- Docker image
- Youtube Channel
- So, You Want to Build a Superset Viz Plugin...